Contrast restoration of foggy images on the ZYNQ embedded platform

Bogdan Coseriu, M. Negru, S. Nedevschi
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引用次数: 5

Abstract

Autonomous Vehicles require accurate environment information in order to perform scene understanding with very high accuracy. For this reason, we must design perception algorithms that are robust and must perform in any environmental and weather conditions. Since fog is one of the most dangerous weather phenomena for driving we propose an embedded solution that is able to restore the contrast of images captured from a moving vehicle in fog conditions. Our solution is based on a state of the art contrast restoration algorithm and is able to provide high quality images in real time. The visibility in the enhanced images is greatly improved such that other image processing algorithms can be applied on the resulting images. We have chosen the Xilinx ZYNQ embedded platform since it provides the best tradeoff in terms of cost, performance and form-factor.
基于ZYNQ嵌入式平台的雾天图像对比度恢复
自动驾驶汽车需要准确的环境信息,才能以非常高的精度进行场景理解。出于这个原因,我们必须设计出鲁棒的感知算法,并且必须在任何环境和天气条件下都能运行。由于雾是驾驶中最危险的天气现象之一,我们提出了一种嵌入式解决方案,能够恢复在雾条件下从移动车辆捕获的图像的对比度。我们的解决方案基于最先进的对比度恢复算法,能够实时提供高质量的图像。增强图像中的可见性大大提高,使得其他图像处理算法可以应用于所得到的图像。我们选择了Xilinx ZYNQ嵌入式平台,因为它在成本,性能和外形方面提供了最佳的权衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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